Text Classification
Transformers
Safetensors
Korean
bert
smishing
binary-classification
text-embeddings-inference
Instructions to use sseul2/bert-smishing-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sseul2/bert-smishing-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sseul2/bert-smishing-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sseul2/bert-smishing-model") model = AutoModelForSequenceClassification.from_pretrained("sseul2/bert-smishing-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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base_model:
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- google-bert/bert-base-multilingual-cased
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pipeline_tag: text-classification
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---
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# bert-smishing-model
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base_model:
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- google-bert/bert-base-multilingual-cased
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pipeline_tag: text-classification
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license: apache-2.0
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# bert-smishing-model
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